Journal article
An automated image analysis framework for segmentation and division plane detection of single live Staphylococcus aureus cells which can operate at millisecond sampling time scales using bespoke Slimfield microscopy
- Abstract:
- Staphylococcus aureus is an important pathogen, giving rise to antimicrobial resistance in cell strains such as Methicillin Resistant S. aureus (MRSA). Here we report an image analysis framework for automated detection and image segmentation of cells in S. aureus cell clusters, and explicit identification of their cell division planes.Weuse a new combination of several existing analytical tools of image analysis to detect cellular and subcellular morphological features relevant to cell division from millisecond time scale sampled images of live pathogens at a detection precision of single molecules.Wedemonstrate this approach using a fluorescent reporter GFP fused to the protein EzrA that localises to a mid-cell plane during division and is involved in regulation of cell size and division. This image analysis framework presents a valuable platform from which to study candidate new antimicrobials which target the cell division machinery, but may also have more general application in detecting morphologically complex structures of fluorescently labelled proteins present in clusters of other types of cells.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 2.3MB, Terms of use)
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- Publisher copy:
- 10.1088/1478-3975/13/5/055002
Authors
- Publisher:
- Institute of Physics
- Journal:
- Physical Biology More from this journal
- Volume:
- 13
- Issue:
- 5
- Pages:
- 055002
- Publication date:
- 2016-10-17
- Acceptance date:
- 2016-09-07
- DOI:
- EISSN:
-
1478-3975
- ISSN:
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1478-3967
- Keywords:
- Pubs id:
-
pubs:821226
- UUID:
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uuid:c962e580-e0d3-4729-b52a-254f1409a41b
- Local pid:
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pubs:821226
- Source identifiers:
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821226
- Deposit date:
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2018-04-11
Terms of use
- Copyright holder:
- IOP Publishing Ltd
- Copyright date:
- 2016
- Notes:
- ©2016 IOP Publishing Ltd. Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
- Licence:
- CC Attribution (CC BY)
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